A linkage information output apparatus is an apparatus which outputs information (hereinafter, also referred to as linkage information) linked with source information. Hereinafter, the linkage information is made to include a combination of source information and destination information, or a combination of source information, destination information and a relation content.
That is, the linkage information is the information which indicates linkage among keywords, documents, images, and voices. A relation content is a keyword and a sentence which indicate a type and characteristic feature of linkage.
It is important to select information which is unpredictable and attracts an interest as information presented to a user. Because, in the case of Web service etc., presenting information which attracts a user's interest promotes revisit of a user to a Web site, and links directly with the access number to the Web site. In addition, because, also in marketing, acquiring new information which the others cannot perceive easily will acquire new perceiving, and therefore, it is possible to be connected with new product development which is different from that of the others.
An example of a conventional linkage information output apparatus is disclosed in Shingo Otsuka, et al., “one consideration with respect to a detection method of a related term using a global-area web access log”, Journal of Information Processing Society of Japan, vol. 46 No. SIG8 (TOD26), pp. 82-92 (2005) (Non-patent document 1). In Non-patent document 1, source information and destination information are keywords. When linkage information is presented, with a keyword of a linkage source as an input, the keyword having the highest access frequency among keywords which exist in Web pages accessed until now is outputted. Therefore, in the linkage information output apparatus disclosed in Non-patent Document 1, the object is to present the keyword most linked with the source information.
An example of a method of determining whether certain information is information which has unpredictability is disclosed in Yohei Noda, et al., “Relational analysis for unpredictable knowledge discovery among Wikipedia categories”, Society for the study of 20th Semantic Web and Ontology, SIG-SWO-A803-02, pp. 08-01 to pp. 08-04 (2008) (Non-patent document 2). That is, in Non-patent document 2, a method of evaluating whether the information is unpredictable information based on a co-occurrence frequency of two categories is disclosed. Here, information belongs to a plurality of categories, and a co-occurrence frequency of two categories is the number of times where two categories belong to one of information concurrently. As for information Z which belongs concurrently to two categories with the category co-occurrence frequency small, it is assumed that an unpredictable knowledge over these two categories is included therein. In the case where the information Z is included in any two categories with the co-occurrence frequency small, this information Z is outputted as unpredictable information.
For example, assume that information “Taro Aso” belongs to a category “Prime Minister” and a category “Olympic athlete”. At this time, in the case where the co-occurrence frequency of these two categories is low, the information “Taro Aso” is outputted as an unpredictable information.